Boellaard, R. | bioRxiv Science

bioRxiv2020

DNA methylation classification in diffuse glioma shows little spatial heterogeneity after adjusting for tumor purity

Intratumoral heterogeneity is a hallmark of diffuse gliomas. We used neuronavigation to acquire 133 image-guided and spatially-separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma, which we characterized using DNA methylation arrays. Samples were obtained from regions with and without imaging abnormalities. Methylation profiles were analyzed to devise a three-dimensional reconstruction of genetic and epigenetic heterogeneity. Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and largely explains apparent epigenetic spatial heterogeneity. Indeed, we observed that DNA methylation subtypes are highly conserved in space after adjusting for tumor purity. Genome-wide heterogeneity analysis showed equal or increased heterogeneity among normal tissue when compared to tumor. These findings were validated in a separate cohort of 61 multi-sector tumor and 64 normal samples. Our findings underscore the infiltrative nature of diffuse gliomas and suggest that heterogeneity in DNA methylation is innate to somatic cells and not a characteristic feature of this tumor type.

cancer biology↗

bioRxiv2019

PET and CSF amyloid-β status are differently predicted by patient features: Information from discordant cases

BackgroundAmyloid-{beta} PET and CSF A{beta}42 yield discordant results in 10-20% of patients, possibly providing unique information. Although the predictive power of demographic, clinical, genetic and imaging features for amyloid-positivity has previously been investigated, it is unknown whether these features differentially predict amyloid-{beta} status based on PET or CSF, or whether this differs by disease stage.\n\nMethodsWe included 768 patients (subjective cognitive decline (SCD, n=194), mild cognitive impairment (MCI, n=127), dementia (AD and non-AD, n=447) with amyloid-{beta} PET and CSF A{beta}42 measurement within one year. 97(13%) patients had discordant PET/CSF amyloid-{beta} status. We performed parallel random forest models predicting separately PET and CSF status using 17 patient features (demographics, APOE4 positivity, CSF (p)tau, cognitive performance, and MRI visual ratings) in the total patient group and stratified by syndrome diagnosis. Thereafter, we selected features with the highest variable importance measure (VIM) as input for logistic regression models, where amyloid status on either PET or CSF was predicted by (i) the selected patient feature, and (ii) the patient feature adjusted for the status of the other amyloid modality.\n\nResultsAPOE4, CSF tau and p-tau had highest VIM for PET and CSF in all groups. In the amyloid-adjusted logistic regression models, p-tau was a significant predictor for PET-amyloid in SCD (OR=1.02[1.01-1.04], pFDR=0.03), MCI (OR=1.05[1.02-1.07], pFDR<0.01) and dementia (OR=1.04[1.03-1.05], pFDR<0.001), but not for CSF-amyloid. APOE4 (OR=3.07[1.33-7.07], punc<0.01) was associated with CSF-amyloid in SCD, while it was only predictive for PET-amyloid in MCI (OR=9.44[2.93,30.39], pFDR<0.01). Worse MMSE scores (OR=1.21[1.03-1.41], punc=0.02) were associated to CSF-amyloid status in SCD, whereas worse memory (OR=1.17[1.05-1.31], pFDR=0.02) only predicted PET positivity in dementia.\n\nConclusionAmyloid status based on either PET or CSF was predicted by different patient features and this varied by disease stage, suggesting that PET-CSF discordance yields unique information. The stronger associations of both APOE4 carriership and worse memory z-scores with CSF-amyloid in SCD suggests that CSF-amyloid is more sensitive early in the disease course. The higher predictive value of CSF p-tau for a positive PET scan suggests that PET is more specific to AD pathology. These findings can influence the choice between amyloid biomarkers in future studies or trials.

neuroscience↗